摘要：生成對抗網絡的各種變體非常多，的發明者在上推薦了這份名為的各種變體列表，這也表明現在確實非常火，被應用于各種各樣的任務。了解這些各種各樣的，或許能對你創造自己的有所啟發。這篇文章列舉了目前出現的各種變體，并將長期更新。

生成對抗網絡（GAN）的各種變體非常多，GAN 的發明者 Ian Goodfellow 在Twitter上推薦了這份名為“The GAN Zoo”的各種GAN變體列表，這也表明現在GAN確實非?；穑粦糜诟鞣N各樣的任務。了解這些各種各樣的GAN，或許能對你創造自己的 X-GAN有所啟發。

幾乎每周都有新的關于生成對抗網絡（GAN）的論文出現，而且你很難跟蹤到它們，因為研究者為這些 GAN 命名的方式非常具有創造性。了解有關 GAN 的更多信息，可以參考 OpenAI 博客的一份非常全面的 GAN 綜述文章（地址：https://blog.openai.com/generative-models/），或閱讀王飛躍等人的 GAN 綜述文章。

這篇文章列舉了目前出現的各種GAN變體，并將長期更新。這是一個開源的項目，你也可以通過 pull request 添加作者沒有注意到的 GAN，

GitHub 地址：https://github.com/hindupuravinash/the-gan-zoo

這份列表的形式是：名稱——論文標題（論文均發表在Arxiv，也可在深度學習世界公眾號回復【變體論文】下載）。

GAN?—?Generative Adversarial Networks

3D-GAN?—?Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling

AdaGAN?—?AdaGAN: Boosting Generative Models

AffGAN?—?Amortised MAP Inference for Image Super-resolution

ALI?—?Adversarially Learned Inference

AMGAN?—?Generative Adversarial Nets with Labeled Data by Activation Maximization

AnoGAN?—?Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery

ArtGAN?—?ArtGAN: Artwork Synthesis with Conditional Categorial GANs

b-GAN?—?b-GAN: Unified Framework of Generative Adversarial Networks

Bayesian GAN?—?Deep and Hierarchical Implicit Models

BEGAN?—?BEGAN: Boundary Equilibrium Generative Adversarial Networks

BiGAN?—?Adversarial Feature Learning

BS-GAN?—?Boundary-Seeking Generative Adversarial Networks

CGAN?—?Towards Diverse and Natural Image Descriptions via a Conditional GAN

CCGAN?—?Semi-Supervised Learning with Context-Conditional Generative Adversarial Networks

CatGAN?—?Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks

CoGAN?—?Coupled Generative Adversarial Networks

Context-RNN-GAN?—?Contextual RNN-GANs for Abstract Reasoning Diagram Generation

C-RNN-GAN?—?C-RNN-GAN: Continuous recurrent neural networks with adversarial training

CVAE-GAN?—?CVAE-GAN: Fine-Grained Image Generation through Asymmetric Training

CycleGAN?—?Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

DTN?—?Unsupervised Cross-Domain Image Generation

DCGAN?—?Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks

DiscoGAN?—?Learning to Discover Cross-Domain Relations with Generative Adversarial Networks

DualGAN?—?DualGAN: Unsupervised Dual Learning for Image-to-Image Translation

EBGAN?—?Energy-based Generative Adversarial Network

f-GAN?—?f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization

GoGAN?—?Gang of GANs: Generative Adversarial Networks with Maximum Margin Ranking

GP-GAN?—?GP-GAN: Towards Realistic High-Resolution Image Blending

IAN?—?Neural Photo Editing with Introspective Adversarial Networks

iGAN?—?Generative Visual Manipulation on the Natural Image Manifold

IcGAN?—?Invertible Conditional GANs for image editing

ID-CGAN — Image De-raining Using a Conditional Generative Adversarial Network

Improved GAN?—?Improved Techniques for Training GANs

InfoGAN?—?InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets

LR-GAN?—?LR-GAN: Layered Recursive Generative Adversarial Networks for Image Generation

LSGAN?—?Least Squares Generative Adversarial Networks

LS-GAN?—?Loss-Sensitive Generative Adversarial Networks on Lipschitz Densities

MGAN?—?Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks

MAGAN?—?MAGAN: Margin Adaptation for Generative Adversarial Networks

MalGAN?—?Generating Adversarial Malware Examples for Black-Box Attacks Based on GAN

MARTA-GAN?—?Deep Unsupervised Representation Learning for Remote Sensing Images

McGAN?—?McGan: Mean and Covariance Feature Matching GAN

MedGAN?—?Generating Multi-label Discrete Electronic Health Records using Generative Adversarial Networks

MIX+GAN?—?Generalization and Equilibrium in Generative Adversarial Nets (GANs)

MPM-GAN?—?Message Passing Multi-Agent GANs

MV-BiGAN?—?Multi-view Generative Adversarial Networks

pix2pix?—?Image-to-Image Translation with Conditional Adversarial Networks

PPGN?—?Plug & Play Generative Networks: Conditional Iterative Generation of Images in Latent Space

PrGAN?—?3D Shape Induction from 2D Views of Multiple Objects

RenderGAN?—?RenderGAN: Generating Realistic Labeled Data

RTT-GAN?—?Recurrent Topic-Transition GAN for Visual Paragraph Generation

SGAN?—?Stacked Generative Adversarial Networks

SGAN?—?Texture Synthesis with Spatial Generative Adversarial Networks

SAD-GAN?—?SAD-GAN: Synthetic Autonomous Driving using Generative Adversarial Networks

SalGAN?—?SalGAN: Visual Saliency Prediction with Generative Adversarial Networks

SEGAN?—?SEGAN: Speech Enhancement Generative Adversarial Network

SeqGAN?—?SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient

SketchGAN?—?Adversarial Training For Sketch Retrieval

SL-GAN?—?Semi-Latent GAN: Learning to generate and modify facial images from attributes

SRGAN?—?Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network

S2GAN?—?Generative Image Modeling using Style and Structure Adversarial Networks

SSL-GAN?—?Semi-Supervised Learning with Context-Conditional Generative Adversarial Networks

StackGAN?—?StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks

TGAN?—?Temporal Generative Adversarial Nets

TAC-GAN?—?TAC-GAN?—?Text Conditioned Auxiliary Classifier Generative Adversarial Network

TP-GAN?—?Beyond Face Rotation: Global and Local Perception GAN for Photorealistic and Identity Preserving Frontal View Synthesis

Triple-GAN?—?Triple Generative Adversarial Nets

VGAN?—?Generative Adversarial Networks as Variational Training of Energy Based Models

VAE-GAN?—?Autoencoding beyond pixels using a learned similarity metric

ViGAN?—?Image Generation and Editing with Variational Info Generative AdversarialNetworks

WGAN?—?Wasserstein GAN

WGAN-GP?—?Improved Training of Wasserstein GANs

WaterGAN?—?WaterGAN: Unsupervised Generative Network to Enable Real-time Color Correction of Monocular Underwater Images

原文地址：https://deephunt.in/the-gan-zoo-79597dc8c347

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